Back To Course

Physical Science: Middle School9 chapters | 61 lessons

Are you a student or a teacher?

Try Study.com, risk-free

As a member, you'll also get unlimited access to over 75,000 lessons in math, English, science, history, and more. Plus, get practice tests, quizzes, and personalized coaching to help you succeed.

Try it risk-freeWhat teachers are saying about Study.com

Already registered? Login here for access

Your next lesson will play in
10 seconds

Lesson Transcript

Instructor:
*David Wood*

David has taught Honors Physics, AP Physics, IB Physics and general science courses. He has a Masters in Education, and a Bachelors in Physics.

After watching this video, you should be able to explain what a graph is, construct a scatter plot, and interpret scatter plots from scientific data. A short quiz will follow.

In science, a **graph** is a way of presenting the data collected in an experiment, showing how one variable affects another variable. Experiments are the heart of science; they're how we analyze and understand the world. Scientists refuse to make claims about the world unless they have some hard data, some numbers on which to base that claim. And science experiments are how we get that data.

A **science experiment** is a way of figuring out the structure and behavior of the world using a systematic method. In any experiment, you change one variable (called **the independent variable**), and see how it affects another variable (called **the dependent variable**). Everything else must be kept the same, otherwise it won't be a fair test.

For example, you might want to test how many fruit grow on trees when they're watered by different amounts. The independent variable you're changing is the amount of water the plants get, and the resulting dependent variable you're looking at is how many fruit grow. For this experiment to lead to useful data, everything else must be kept the same. The plants must be in the same kind of soil with the same sunlight. Otherwise, your data would be meaningless because you wouldn't know if the type of soil, amount of sunlight, or other factor was actually causing your result.

Once we have our data, it's time to analyze it. It's time to find the relationship between the two variables.

Graphs are the standard way to present data in science. The most common kind of graph we use to look at the relationship between two variables is called a **scatter plot**. A scatter plot is where the numbers are plotted on a set of axes by drawing a cross for each of the pieces of data. The independent variable is always plotted on the *x*-axis, which is the horizontal axis. And the dependent variable is always plotted on the *y*-axis, which is the vertical axis.

Once you have all your data points, you can draw a line of best fit through the data. A line of best fit isn't actually a straight line. It might be, but it can also be a curve. And a line of best fit doesn't have to go through every data point; in fact, it usually will miss most of the data points. It's just a line that best represents the general shape of the data. Here are a few examples:

Once we have our scatter plot and line of best fit, it's time to **interpret** the data, or explain what the data shows.

If the data is completely random and no line of best fit could be drawn, you can say that there is no relationship between the two variables. In our original experiment, for example, this would be like finding that the amount of water made no difference in how many fruit grew on the plant.

If the line of best fit is flat, meaning that it doesn't go uphill or downhill, there is still no relationship between the two variables. This would be what your graph would look like if no matter how much you watered a plant, they all grew exactly the same number of fruit:

If the line of best fit is straight and diagonal, this means that there does appear to be some kind of relationship between the two variables. To be exact, there is a linear relationship. You can also make a statement about how one variable relates to the other.

For example, you might say that the more you water a plant, the more fruit grow, which would be an uphill slope on the graph (a positive linear relationship). Or you might say that the less you water a plant, the more fruit grow, which would be a downhill slope on the graph (a negative linear relationship). Since the graph is a straight line, you can also say that doubling the amount of water you use will always have the same effect on the number of fruit that grow.

Last of all, if the line of best fit is curved, this also means that there is a relationship between the two variables, but that it is a nonlinear relationship. This might mean, for example, that the more you water a plant, the more fruit grow, but once you get to a certain point, it makes less and less of a difference.

When interpreting a graph in science, we have to be really careful. Even if there is a nice, neat line on our graph, it doesn't mean that the two variables affect each other. For example, maybe when the person came to water the plants, he accidentally dropped some fertilizer onto the plants from his shoes, and THAT'S why they grew more. So you have to be careful about the conclusions you make. Or in science language: correlation doesn't always equal causation.

In science, a **graph** is a way of presenting the data collected in an experiment, showing how one variable affects another variable. Experiments are the heart of science; they're how we analyze and understand the world. In a science experiment, you change one variable (called the **independent variable**), and see how it affects another variable (called the **dependent variable**). Everything else must be kept the same, otherwise it won't be a fair test.

Graphs are the standard way to present data in science. The most common kind of graph we use to look at the relationship between two variables is called a **scatter plot**. A scatter plot is where the numbers are plotted on a set of axes by drawing a cross for each of the pieces of data. The independent variable is always plotted on the *x*-axis, which is the horizontal axis. And the dependent variable is always plotted on the *y*-axis, which is the vertical axis.

Once you have all your data points, you can draw a line of best fit through the data. A line of best fit isn't actually a straight line. It might be, but it can also be a curve. A line of best fit doesn't have to go through every data point; in fact, it usually will miss most of the data points. It's just a line that best represents the general shape of the data.

Once we have our scatter plot and line of best fit, it's time to **interpret** the data, or explain what the data shows. The data might show no relationship, either because the points are scattered randomly or because the line of best fit is flat. This shows that the variables don't affect each other. A diagonal line means there is a linear relationship. This means that as one variable goes up, the other either goes up, or goes down. It also means that if you double one variable, the other will always go up by the same amount. Last of all, if the line of best fit is curved, this also means that there is a relationship between the two variables but that it is a nonlinear relationship.

When interpreting a graph in science, we have to be really careful. Even if there is a nice, neat line on our graph, it doesn't mean that the two variables affect each other. There could be another reason they changed together. Remember: correlation doesn't always equal causation.

Once you've completed this lesson, you should be able to:

- Identify the importance of experiments and graphs in science
- Recall how to construct a scatter plot and line of best fit
- Explain how to interpret a scatter plot
- Describe considerations to keep in mind when interpreting data on a graph

To unlock this lesson you must be a Study.com Member.

Create your account

Are you a student or a teacher?

Already a member? Log In

BackWhat teachers are saying about Study.com

Already registered? Login here for access

Did you know… We have over 160 college courses that prepare you to earn credit by exam that is accepted by over 1,500 colleges and universities. You can test out of the first two years of college and save thousands off your degree. Anyone can earn credit-by-exam regardless of age or education level.

To learn more, visit our Earning Credit Page

Not sure what college you want to attend yet? Study.com has thousands of articles about every imaginable degree, area of study and career path that can help you find the school that's right for you.

You are viewing lesson
Lesson
7 in chapter 9 of the course:

Back To Course

Physical Science: Middle School9 chapters | 61 lessons

- Go to Reactions

- The Scientific Method: Steps, Terms & Examples 8:43
- Experimental Design in Science: Definition & Method 8:30
- Evaluating Data from Scientific Investigation 4:31
- Variables & Controls in a Science Experiment 4:45
- Measures of Central Tendency: Definitions & Practice 5:25
- How to Read Scientific Graphs & Charts 9:49
- How to Construct Graphs from Data & Interpret Them 6:31
- Solve for Unknowns in Scientific Equations 4:24
- Go to Investigation & Experimentation in Physical Science

- Computer Science 335: Mobile Forensics
- Electricity, Physics & Engineering Lesson Plans
- Teaching Economics Lesson Plans
- U.S. Politics & Civics Lesson Plans
- US History - Civil War: Lesson Plans & Resources
- iOS Data Analysis & Recovery
- Acquiring Data from iOS Devices
- Foundations of Digital Forensics
- Introduction to Mobile Forensics
- Examination of iOS Devices
- CNE Prep Product Comparison
- IAAP CAP Prep Product Comparison
- TACHS Prep Product Comparison
- Top 50 Blended Learning High Schools
- EPPP Prep Product Comparison
- NMTA Prep Product Comparison
- Study.com NMTA Scholarship: Application Form & Information

- History of Sparta
- Realistic vs Optimistic Thinking
- How Language Reflects Culture & Affects Meaning
- Logical Thinking & Reasoning Questions: Lesson for Kids
- Human Geography Project Ideas
- Asian Heritage Month Activities
- Types of Visualization in Python
- Quiz & Worksheet - Frontalis Muscle
- Octopus Diet: Quiz & Worksheet for Kids
- Quiz & Worksheet - Fezziwig in A Christmas Carol
- Quiz & Worksheet - Dolphin Mating & Reproduction
- Flashcards - Measurement & Experimental Design
- Flashcards - Stars & Celestial Bodies
- ESL Conversation Questions & Topics for ESL Students
- Geometry Worksheets

- ILTS Social Science - Sociology and Anthropology (249): Test Practice and Study Guide
- DSST Organizational Behavior: Study Guide & Test Prep
- High School Precalculus: Help and Review
- Intro to Criminal Justice: Help and Review
- History 104: US History II
- Government Regulation of Business
- Types of Government
- Quiz & Worksheet - Self-Regulation Theory
- Quiz & Worksheet - Key Components of Physical Health
- Quiz & Worksheet - Plant Cell Membrane
- Quiz & Worksheet - Pros & Cons of Genetic Manipulation
- Quiz & Worksheet - Process of Plant Fertilization

- Subsistence Farming: Definition & Examples
- Finding the Inverse of a 3x3 Matrix
- Earth Day Poster Ideas
- Can You Use a Calculator on the GMAT?
- Can You Use a Calculator on the GMAT?
- Where Can I Find Free SAT Questions?
- When Do You Take the PSAT?
- How to Ace the GMAT
- Homeschooling in New Jersey
- Romeo and Juliet Act 3 Lesson Plan
- How to Ace a Nursing Interview
- LSAT Test Dates

- Tech and Engineering - Videos
- Tech and Engineering - Quizzes
- Tech and Engineering - Questions & Answers

Browse by subject